360VIO: A Robust Visual-Inertial Odometry Using a 360-Degree Camera

To evaluate the proposed odometry method based on 360-degree cameras, we build a new dataset using an Insta-360 One X2 device, which provided high-resolution 4K images captured at a rate of 30 frames per second and 500\,Hz IMU measurements from its built-in IMU.Different from previous datasets, we have set the illumination brightness and the camera movements as the condition variable. The sequence can be classified based on changes in illumination speed or camera movement intensity. The changes in illumination condition can be classified into normal light(N), illumination change light(IC) and low(L) light based on the brightness of the lights. This dataset can effectively demonstrate the efficacy of the algorithm and the benefits brought by the 360 degree camera.

为评估所提出的基于360°相机的里程计方法，我们使用Insta-360 One X2设备构建了全新数据集。该设备可采集帧率为30帧/秒的高分辨率4K图像，以及内置惯性测量单元（IMU）的500Hz惯性测量数据。与此前的各类数据集不同，我们将光照亮度与相机运动设置为条件变量。该数据集序列可依据光照变化速率或相机运动强度进行分类。光照条件可根据光线亮度划分为正常光照（N）、光照变化（IC）与低光照（L）三类。本数据集可有效验证所提算法的性能，并体现360°相机带来的应用优势。

搜集汇总

背景与挑战

背景概述

该数据集名为“360VIO: A Robust Visual-Inertial Odometry Using a 360-Degree Camera”，旨在评估基于360度相机的视觉-惯性里程计方法。数据集使用Insta-360 One X2设备采集，包含高分辨率4K图像（30帧/秒）和500 Hz的IMU测量，并特别设计了光照亮度（正常、变化、低光）和相机运动强度作为变量，以测试算法在不同条件下的鲁棒性。